{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "70b3db6b-8907-4b78-9523-e2cdc102e2af",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "122ea2a7-0562-4266-9bc5-7982e79a2c28",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://mirrors.aliyun.com/pypi/simple/\n",
      "Collecting matplotlib\n",
      "  Downloading https://mirrors.aliyun.com/pypi/packages/01/75/6c7ce560e95714a10fcbb3367d1304975a1a3e620f72af28921b796403f3/matplotlib-3.9.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.3 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.3/8.3 MB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[?25hCollecting contourpy>=1.0.1 (from matplotlib)\n",
      "  Downloading https://mirrors.aliyun.com/pypi/packages/03/33/003065374f38894cdf1040cef474ad0546368eea7e3a51d48b8a423961f8/contourpy-1.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (323 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m323.2/323.2 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
      "\u001b[?25hCollecting cycler>=0.10 (from matplotlib)\n",
      "  Downloading https://mirrors.aliyun.com/pypi/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl (8.3 kB)\n",
      "Collecting fonttools>=4.22.0 (from matplotlib)\n",
      "  Downloading https://mirrors.aliyun.com/pypi/packages/96/13/748b7f7239893ff0796de11074b0ad8aa4c3da2d9f4d79a128b0b16147f3/fonttools-4.54.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.9 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.9/4.9 MB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[?25hCollecting kiwisolver>=1.3.1 (from matplotlib)\n",
      "  Downloading https://mirrors.aliyun.com/pypi/packages/a7/4b/2db7af3ed3af7c35f388d5f53c28e155cd402a55432d800c543dc6deb731/kiwisolver-1.4.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m1.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: numpy>=1.23 in /usr/lib64/python3.11/site-packages (from matplotlib) (2.1.2)\n",
      "Requirement already satisfied: packaging>=20.0 in /usr/lib/python3.11/site-packages (from matplotlib) (24.1)\n",
      "Collecting pillow>=8 (from matplotlib)\n",
      "  Downloading https://mirrors.aliyun.com/pypi/packages/39/63/b3fc299528d7df1f678b0666002b37affe6b8751225c3d9c12cf530e73ed/pillow-11.0.0-cp311-cp311-manylinux_2_28_x86_64.whl (4.4 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.4/4.4 MB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: pyparsing>=2.3.1 in /usr/lib/python3.11/site-packages (from matplotlib) (3.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /usr/lib/python3.11/site-packages (from matplotlib) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /usr/lib/python3.11/site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
      "Installing collected packages: pillow, kiwisolver, fonttools, cycler, contourpy, matplotlib\n",
      "Successfully installed contourpy-1.3.0 cycler-0.12.1 fonttools-4.54.1 kiwisolver-1.4.7 matplotlib-3.9.2 pillow-11.0.0\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "429dac51-2096-4723-9b57-f70700604822",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 创建一个DiGraph对象\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# 添加节点\n",
    "G.add_node('A')\n",
    "G.add_node('B')\n",
    "G.add_node('C')\n",
    "G.add_node('D')\n",
    "G.add_node('E')\n",
    "\n",
    "# 添加边\n",
    "G.add_edge('A', 'B')\n",
    "G.add_edge('A', 'C')\n",
    "G.add_edge('B', 'D')\n",
    "G.add_edge('B', 'E')\n",
    "\n",
    "# 绘制层次图\n",
    "nx.draw(G, with_labels=True, node_size=800, node_color='lightblue', node_shape='s', alpha=0.8, font_size=12, font_color='k', font_weight='bold', width=2, edge_color='gray')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8a1fb958-5699-4cfc-9699-a80508d31b7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 创建一个DiGraph对象\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# 添加节点和层次关系\n",
    "G.add_node('A', level=0)\n",
    "G.add_node('B', level=1)\n",
    "G.add_node('C', level=1)\n",
    "G.add_node('D', level=2)\n",
    "G.add_node('E', level=2)\n",
    "\n",
    "# 添加边\n",
    "G.add_edge('A', 'B')\n",
    "G.add_edge('A', 'C')\n",
    "G.add_edge('B', 'D')\n",
    "G.add_edge('B', 'E')\n",
    "\n",
    "# 使用层次布局\n",
    "pos = nx.shell_layout(G)\n",
    "# 绘制层次图\n",
    "nx.draw(G, pos, with_labels=True, node_size=800, node_color='lightblue', node_shape='s', alpha=0.8, font_size=12, font_color='k', font_weight='bold', width=2, edge_color='gray')\n",
    "# 显示图形\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8c61cd1f-b28c-4fbf-a3fc-86acf6fcb715",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://mirrors.aliyun.com/pypi/simple/\n",
      "Collecting pygraphviz\n",
      "  Using cached https://mirrors.aliyun.com/pypi/packages/66/ca/823d5c74a73d6b8b08e1f5aea12468ef334f0732c65cbb18df2a7f285c87/pygraphviz-1.14.tar.gz (106 kB)\n",
      "  Installing build dependencies ... \u001b[?25ldone\n",
      "\u001b[?25h  Getting requirements to build wheel ... \u001b[?25ldone\n",
      "\u001b[?25h  Preparing metadata (pyproject.toml) ... \u001b[?25ldone\n",
      "\u001b[?25hBuilding wheels for collected packages: pygraphviz\n",
      "  Building wheel for pygraphviz (pyproject.toml) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for pygraphviz: filename=pygraphviz-1.14-cp311-cp311-linux_x86_64.whl size=170890 sha256=89db9eeabf5a731cb68f695938b914523171619371d096f9446af5f1a1fe230f\n",
      "  Stored in directory: /root/.cache/pip/wheels/f8/bc/f8/ba050223d38e70355bdb1c783450f82243d32109c69113b509\n",
      "Successfully built pygraphviz\n",
      "Installing collected packages: pygraphviz\n",
      "Successfully installed pygraphviz-1.14\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# yum install -y gcc python3-devel graphviz graphviz-devel\n",
    "%pip install pygraphviz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dc6ea1ab-4b27-4e74-9324-14bfa27c9416",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 创建有向图\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# 添加节点和层次关系\n",
    "G.add_node('A', level=0)\n",
    "G.add_node('B', level=1)\n",
    "G.add_node('C', level=1)\n",
    "G.add_node('D', level=2)\n",
    "G.add_node('E', level=2)\n",
    "\n",
    "# 添加边\n",
    "G.add_edge('A', 'B')\n",
    "G.add_edge('A', 'C')\n",
    "G.add_edge('B', 'D')\n",
    "G.add_edge('B', 'E')\n",
    "\n",
    "# 使用 pygraphviz 进行层次布局\n",
    "A = nx.nx_agraph.to_agraph(G)\n",
    "A.layout('dot')  # 使用 dot 布局\n",
    "\n",
    "# 绘制图形\n",
    "A.draw('graph.png')  # 保存为图像文件\n",
    "img = plt.imread('graph.png')\n",
    "plt.imshow(img)\n",
    "plt.axis('off')  # 不显示坐标轴\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4c07c9a7-e5ba-4660-96bb-a9bcd7a86b4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hoverinfo": "none",
         "line": {
          "color": "#888",
          "width": 0.5
         },
         "mode": "lines",
         "type": "scatter",
         "x": [
          0,
          -1,
          null,
          0,
          1,
          null,
          -1,
          -1.5,
          null,
          -1,
          -0.5,
          null
         ],
         "y": [
          0,
          -1,
          null,
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     "metadata": {},
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   ],
   "source": [
    "# !pip install plotly\n",
    "import networkx as nx\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# 创建有向图\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# 添加节点和层次关系\n",
    "G.add_node('A', level=0)\n",
    "G.add_node('B', level=1)\n",
    "G.add_node('C', level=1)\n",
    "G.add_node('D', level=2)\n",
    "G.add_node('E', level=2)\n",
    "\n",
    "# 添加边\n",
    "G.add_edge('A', 'B')\n",
    "G.add_edge('A', 'C')\n",
    "G.add_edge('B', 'D')\n",
    "G.add_edge('B', 'E')\n",
    "\n",
    "# 定义分层位置\n",
    "pos = {\n",
    "    'A': (0, 0),    # Level 0\n",
    "    'B': (-1, -1),  # Level 1\n",
    "    'C': (1, -1),   # Level 1\n",
    "    'D': (-1.5, -2), # Level 2\n",
    "    'E': (-0.5, -2)  # Level 2\n",
    "}\n",
    "\n",
    "# 获取节点位置\n",
    "x_nodes = [pos[n][0] for n in G.nodes()]\n",
    "y_nodes = [pos[n][1] for n in G.nodes()]\n",
    "\n",
    "# 创建边的坐标\n",
    "edge_x = []\n",
    "edge_y = []\n",
    "for edge in G.edges():\n",
    "    x0, y0 = pos[edge[0]]\n",
    "    x1, y1 = pos[edge[1]]\n",
    "    edge_x.append(x0)\n",
    "    edge_x.append(x1)\n",
    "    edge_x.append(None)  # None 用于分隔边\n",
    "    edge_y.append(y0)\n",
    "    edge_y.append(y1)\n",
    "    edge_y.append(None)  # None 用于分隔边\n",
    "\n",
    "# 创建节点的散点图\n",
    "node_trace = go.Scatter(\n",
    "    x=x_nodes, y=y_nodes,\n",
    "    mode='markers+text',\n",
    "    text=list(G.nodes()),\n",
    "    textposition=\"bottom center\",\n",
    "    marker=dict(\n",
    "        showscale=True,\n",
    "        colorscale='YlGnBu',\n",
    "        size=10,\n",
    "        color=[],\n",
    "        line_width=2)\n",
    ")\n",
    "\n",
    "# 创建边的散点图\n",
    "edge_trace = go.Scatter(\n",
    "    x=edge_x, y=edge_y,\n",
    "    line=dict(width=0.5, color='#888'),\n",
    "    hoverinfo='none',\n",
    "    mode='lines'\n",
    ")\n",
    "\n",
    "# 创建图形\n",
    "fig = go.Figure(data=[edge_trace, node_trace],\n",
    "             layout=go.Layout(\n",
    "                title='Layered Interactive Network Graph',\n",
    "                titlefont_size=16,\n",
    "                showlegend=False,\n",
    "                hovermode='closest',\n",
    "                margin=dict(b=0,l=0,r=0,t=40),\n",
    "                xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),\n",
    "                yaxis=dict(showgrid=False, zeroline=False, showticklabels=False))\n",
    "             )\n",
    "\n",
    "# 显示图形\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a244cec8-9942-433a-aff1-d6e14474006b",
   "metadata": {},
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    "import plotly.express as px\n",
    "import pandas as pd\n",
    "\n",
    "# 创建示例数据\n",
    "data = {\n",
    "    'Fruit': ['Apples', 'Oranges', 'Bananas', 'Grapes', 'Pineapples'],\n",
    "    'Amount': [10, 15, 7, 12, 5],\n",
    "    'City': ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Phoenix']\n",
    "}\n",
    "\n",
    "# 将数据转换为 DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# 创建交互式散点图\n",
    "fig = px.scatter(df, x='Fruit', y='Amount', color='City', size='Amount',\n",
    "                 title='Fruit Amount by City',\n",
    "                 labels={'Amount': 'Amount of Fruit', 'Fruit': 'Type of Fruit'},\n",
    "                 hover_name='City')\n",
    "\n",
    "fig.write_html('interactive_scatter_plot.html')\n",
    "# 显示图形\n",
    "fig.show()"
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   "source": [
    "import networkx as nx\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# 创建一个有向图\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# 添加节点\n",
    "G.add_nodes_from([\"nginx\", \"server1\", \"server2\"])\n",
    "G.add_nodes_from([\"tomcat\", \"serverApp1\", \"serverApp2\"])\n",
    "G.add_nodes_from([\"mysql\", \"serverDB1\", \"serverDB2\", \"serverDB3\"])\n",
    "\n",
    "# 添加边\n",
    "G.add_edges_from([(\"nginx\", \"server1\"), (\"nginx\", \"server2\")])\n",
    "G.add_edges_from([(\"tomcat\", \"serverApp1\"), (\"tomcat\", \"serverApp2\")])\n",
    "G.add_edges_from([(\"mysql\", \"serverDB1\"), (\"mysql\", \"serverDB2\"), (\"mysql\", \"serverDB3\")])\n",
    "G.add_edges_from([(\"server1\", \"tomcat\"), (\"server2\", \"tomcat\")])\n",
    "G.add_edges_from([(\"serverApp1\", \"mysql\"), (\"serverApp2\", \"mysql\")])\n",
    "\n",
    "# 定义每个节点的层次\n",
    "subset_key = {\n",
    "    \"WEB\": [\"nginx\", \"server1\", \"server2\"],\n",
    "    \"应用\": [\"tomcat\", \"serverApp1\", \"serverApp2\"],\n",
    "    \"数据\": [\"mysql\", \"serverDB1\", \"serverDB2\", \"serverDB3\"]\n",
    "}\n",
    "\n",
    "# 生成布局\n",
    "pos = nx.multipartite_layout(G, subset_key=subset_key)\n",
    "\n",
    "# 提取节点和边\n",
    "edge_x = []\n",
    "edge_y = []\n",
    "for edge in G.edges():\n",
    "    x0, y0 = pos[edge[0]]\n",
    "    x1, y1 = pos[edge[1]]\n",
    "    edge_x.append(x0)\n",
    "    edge_x.append(x1)\n",
    "    edge_x.append(None)  # None用于分隔边\n",
    "    edge_y.append(y0)\n",
    "    edge_y.append(y1)\n",
    "    edge_y.append(None)\n",
    "\n",
    "node_x = []\n",
    "node_y = []\n",
    "for node in G.nodes():\n",
    "    x, y = pos[node]\n",
    "    node_x.append(x)\n",
    "    node_y.append(y)\n",
    "\n",
    "# 创建边的图形\n",
    "edge_trace = go.Scatter(\n",
    "    x=edge_x, y=edge_y,\n",
    "    line=dict(width=0.5, color='#888'),\n",
    "    hoverinfo='none',\n",
    "    mode='lines')\n",
    "\n",
    "# 创建节点的图形\n",
    "node_trace = go.Scatter(\n",
    "    x=node_x, y=node_y,\n",
    "    mode='markers+text',\n",
    "    text=list(G.nodes()),\n",
    "    textposition=\"bottom center\",\n",
    "    marker=dict(\n",
    "        showscale=True,\n",
    "        colorscale='YlGnBu',\n",
    "        size=10,\n",
    "        color=[],\n",
    "        colorbar=dict(thickness=15, title=\"Node Connections\", xanchor='left', titleside='right'),\n",
    "        line_width=2))\n",
    "\n",
    "# 创建图形布局\n",
    "fig = go.Figure(data=[edge_trace, node_trace],\n",
    "             layout=go.Layout(\n",
    "                title='分层应用结构图',\n",
    "                titlefont=dict(size=16),\n",
    "                showlegend=False,\n",
    "                hovermode='closest',\n",
    "                margin=dict(b=0,l=0,r=0,t=40),\n",
    "                xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),\n",
    "                yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)))\n",
    "\n",
    "# 显示图形\n",
    "fig.show()"
   ]
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     },
     "metadata": {},
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   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "# 定义节点\n",
    "labels = [\n",
    "    \"WEB层\", \"nginx\", \"server1\", \"server2\",\n",
    "    \"应用层\", \"tomcat\", \"serverApp1\", \"serverApp2\",\n",
    "    \"数据层\", \"mysql\", \"serverDB1\", \"serverDB2\", \"serverDB3\"\n",
    "]\n",
    "\n",
    "# 定义流动的来源和目标\n",
    "source = [\n",
    "    0, 1, 1, 1,  # WEB层到nginx和server\n",
    "    4, 5, 5, 5,  # 应用层到tomcat和serverApp\n",
    "    8, 9, 9, 9   # 数据层到mysql和serverDB\n",
    "]\n",
    "target = [\n",
    "    1, 2, 3, 4,  # nginx到server1, server2\n",
    "    5, 6, 7, 8,  # tomcat到serverApp1, serverApp2\n",
    "    9, 10, 11, 12  # mysql到serverDB1, serverDB2, serverDB3\n",
    "]\n",
    "value = [8, 4, 4, 8,  # WEB层流动量\n",
    "         4, 2, 2, 2,  # 应用层流动量\n",
    "         2, 2, 2, 2]  # 数据层流动量\n",
    "\n",
    "# 创建桑基图\n",
    "fig = go.Figure(data=[go.Sankey(\n",
    "    node=dict(\n",
    "        pad=15,\n",
    "        thickness=20,\n",
    "        line=dict(color=\"black\", width=0.5),\n",
    "        label=labels,\n",
    "        color=\"blue\"\n",
    "    ),\n",
    "    link=dict(\n",
    "        source=source,\n",
    "        target=target,\n",
    "        value=value\n",
    "    ))])\n",
    "\n",
    "# 设置图形布局\n",
    "fig.update_layout(title_text=\"分层应用结构的桑基图\", font_size=10)\n",
    "\n",
    "# 显示图形\n",
    "fig.show()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 31,
   "id": "b2a84387-4281-4707-904f-673b93827e0d",
   "metadata": {},
   "outputs": [
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    "import plotly.graph_objects as go\n",
    "\n",
    "# 定义节点\n",
    "labels = [\n",
    "    \"WEB层\", \"nginx\", \"server1\", \"server2\",\n",
    "    \"应用层\", \"tomcat\", \"serverApp1\", \"serverApp2\",\n",
    "    \"数据层\", \"mysql\", \"serverDB1\", \"serverDB2\", \"serverDB3\"\n",
    "]\n",
    "\n",
    "# 定义流动的来源和目标\n",
    "source = [\n",
    "    0, 1, 1, 1,  # WEB层到nginx和server\n",
    "    4, 5, 5, 5,  # 应用层到tomcat和serverApp\n",
    "    8, 9, 9, 9   # 数据层到mysql和serverDB\n",
    "]\n",
    "target = [\n",
    "    1, 2, 3, 4,  # nginx到server1, server2\n",
    "    5, 6, 7, 8,  # tomcat到serverApp1, serverApp2\n",
    "    9, 10, 11, 12  # mysql到serverDB1, serverDB2, serverDB3\n",
    "]\n",
    "value = [8, 4, 4, 8,  # WEB层流动量\n",
    "         4, 2, 2, 2,  # 应用层流动量\n",
    "         2, 2, 2, 2]  # 数据层流动量\n",
    "\n",
    "# 定义节点颜色\n",
    "node_colors = [\n",
    "    \"lightblue\",  # WEB层\n",
    "    \"blue\",       # nginx\n",
    "    \"lightgreen\", # server1\n",
    "    \"lightgreen\", # server2\n",
    "    \"lightcoral\", # 应用层\n",
    "    \"red\",        # tomcat\n",
    "    \"orange\",     # serverApp1\n",
    "    \"orange\",     # serverApp2\n",
    "    \"lightyellow\",# 数据层\n",
    "    \"yellow\",     # mysql\n",
    "    \"lightpink\",  # serverDB1\n",
    "    \"lightpink\",  # serverDB2\n",
    "    \"lightpink\"   # serverDB3\n",
    "]\n",
    "\n",
    "# 定义链接颜色\n",
    "link_colors = [\n",
    "    \"rgba(0, 0, 255, 0.5)\",  # WEB层到nginx\n",
    "    \"rgba(0, 255, 0, 0.5)\",  # WEB层到server1\n",
    "    \"rgba(0, 255, 0, 0.5)\",  # WEB层到server2\n",
    "    \"rgba(255, 0, 0, 0.5)\",  # 应用层到tomcat\n",
    "    \"rgba(255, 165, 0, 0.5)\",# 应用层到serverApp1\n",
    "    \"rgba(255, 165, 0, 0.5)\",# 应用层到serverApp2\n",
    "    \"rgba(255, 255, 0, 0.5)\",# 数据层到mysql\n",
    "    \"rgba(255, 192, 203, 0.5)\",# 数据层到serverDB1\n",
    "    \"rgba(255, 192, 203, 0.5)\",# 数据层到serverDB2\n",
    "    \"rgba(255, 192, 203, 0.5)\" # 数据层到serverDB3\n",
    "]\n",
    "\n",
    "# 创建桑基图\n",
    "fig = go.Figure(data=[go.Sankey(\n",
    "    node=dict(\n",
    "        pad=15,\n",
    "        thickness=20,\n",
    "        line=dict(color=\"black\", width=0.5),\n",
    "        label=labels,\n",
    "        color=node_colors\n",
    "    ),\n",
    "    link=dict(\n",
    "        source=source,\n",
    "        target=target,\n",
    "        value=value,\n",
    "        color=link_colors\n",
    "    ))])\n",
    "\n",
    "# 设置图形布局\n",
    "fig.update_layout(title_text=\"分层应用结构的桑基图\", font_size=10)\n",
    "\n",
    "# 显示图形\n",
    "fig.show()"
   ]
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   ],
   "source": [
    "# deepseek的结果\n",
    "import networkx as nx\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# 定义节点\n",
    "labels = [\n",
    "    \"WEB层nginx\", \"server1\", \"server2\", \"server3\", \"sw\",  # WEB层\n",
    "    \"应用层tomcat\", \"serverApp1\", \"serverApp2\", \"swApp\",  # 应用层\n",
    "    \"数据层mysql\", \"serverDB1\", \"serverDB2\", \"serverApp2\"  # 数据层\n",
    "]\n",
    "\n",
    "# 创建图\n",
    "G = nx.DiGraph()\n",
    "\n",
    "# 添加节点\n",
    "for label in labels:\n",
    "    G.add_node(label)\n",
    "\n",
    "# 添加边\n",
    "edges = [\n",
    "    (\"WEB层nginx\", \"server1\"),\n",
    "    (\"WEB层nginx\", \"server2\"),\n",
    "    (\"WEB层nginx\", \"server3\"),\n",
    "    (\"server1\", \"sw\"),\n",
    "    (\"server2\", \"sw\"),\n",
    "    (\"server3\", \"sw\"),\n",
    "    (\"应用层tomcat\", \"serverApp1\"),\n",
    "    (\"应用层tomcat\", \"serverApp2\"),\n",
    "    (\"serverApp1\", \"swApp\"),\n",
    "    (\"serverApp2\", \"swApp\"),\n",
    "    (\"数据层mysql\", \"serverDB1\"),\n",
    "    (\"数据层mysql\", \"serverDB2\"),\n",
    "    (\"数据层mysql\", \"serverApp2\"),\n",
    "    (\"serverDB1\", \"swApp\"),\n",
    "    (\"serverDB2\", \"swApp\"),\n",
    "    (\"serverApp2\", \"swApp\"),\n",
    "    (\"WEB层nginx\", \"应用层tomcat\"),  # WEB层依赖应用层\n",
    "    (\"应用层tomcat\", \"数据层mysql\")  # 应用层依赖数据层\n",
    "]\n",
    "\n",
    "for edge in edges:\n",
    "    G.add_edge(*edge)\n",
    "\n",
    "# 定义颜色\n",
    "colors = {\n",
    "    \"WEB层nginx\": \"rgba(255, 0, 0, 0.5)\",  # 渐变红色\n",
    "    \"应用层tomcat\": \"rgba(0, 255, 0, 0.5)\",  # 渐变绿色\n",
    "    \"数据层mysql\": \"rgba(0, 0, 255, 0.5)\"  # 渐变蓝色\n",
    "}\n",
    "\n",
    "# 定义节点颜色\n",
    "node_colors = [colors.get(node, \"rgba(128, 128, 128, 0.5)\") for node in G.nodes()]\n",
    "\n",
    "# 定义边颜色\n",
    "edge_colors = [colors.get(edge[0], \"rgba(128, 128, 128, 0.5)\") for edge in G.edges()]\n",
    "\n",
    "# 创建桑基图\n",
    "fig = go.Figure(data=[go.Sankey(\n",
    "    node=dict(\n",
    "        pad=15,\n",
    "        thickness=20,\n",
    "        line=dict(color=\"black\", width=0.5),\n",
    "        label=list(G.nodes()),\n",
    "        color=node_colors\n",
    "    ),\n",
    "    link=dict(\n",
    "        source=[labels.index(edge[0]) for edge in G.edges()],\n",
    "        target=[labels.index(edge[1]) for edge in G.edges()],\n",
    "        value=[1] * len(G.edges()),  # 假设每条边的流量为1\n",
    "        color=edge_colors\n",
    "    )\n",
    ")])\n",
    "\n",
    "fig.update_layout(title_text=\"分层应用结构图\", font_size=10)\n",
    "fig.show()"
   ]
  }
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